@article{an_duan_chow_duel-hallen_2019, title={A Distributed and Resilient Bargaining Game for Weather-Predictive Microgrid Energy Cooperation}, volume={15}, ISSN={["1941-0050"]}, url={https://doi.org/10.1109/TII.2019.2907380}, DOI={10.1109/TII.2019.2907380}, abstractNote={A bargaining game is investigated for cooperative energy management in microgrids. This game incorporates a fully distributed and realistic cooperative power scheduling algorithm [cooperative and distributed energy scheduling (CoDES)] as well as a distributed Nash bargaining solution based method of allocating the overall power bill resulting from CoDES. A novel weather-based stochastic renewable generation (RG) prediction method is incorporated in the power scheduling. We demonstrate the proposed game using a four-user grid-connected microgrid model with diverse user demands, storage, and RG profiles and examine the effect of weather prediction on day-ahead power scheduling and cost/profit allocation. Finally, the impact of users’ ambivalence about cooperation and /or dishonesty on the bargaining outcome is investigated, and it is shown that the proposed game is resilient to malicious users’ attempts to avoid payment of their fair share of the overall bill.}, number={8}, journal={IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={An, Lu and Duan, Jie and Chow, Mo-Yuen and Duel-Hallen, Alexandra}, year={2019}, month={Aug}, pages={4721–4730} }
 @article{duan_chow_2020, title={Robust Consensus-Based Distributed Energy Management for Microgrids With Packet Losses Tolerance}, volume={11}, ISSN={["1949-3061"]}, DOI={10.1109/TSG.2019.2921231}, abstractNote={The well-developed consensus algorithm provides an elegant distributed way for solving the energy management problem. The convergence of the consensus-based distributed approach depends on the reliable exchange of the information with neighbors. This assumption might be violated in practice due to inevitable and random packet losses. In this paper, the impact of packet losses on the consensus-based distributed approach is analyzed. We show the iterative calculation converges to an incorrect solution in the presence of packet losses, where the power supply could not meet with the demand. More importantly, we find the error in the final result is accumulated over every packet loss event, and we identify the critical information that cause the error. Based on the analysis, a corrective method is proposed to assure convergence to the right schedule. The corrective method has two features: 1) it uses the original consensus network, and no communication reconfiguration is needed; and 2) no retransmissions for the lost packets are needed, instead, the errors are compensated by a new variable introduced in the update rule. We show that the proposed algorithm could achieve the optimal solution in the presence of packet losses. Numerical simulation results are used to validate the proposed algorithm.}, number={1}, journal={IEEE TRANSACTIONS ON SMART GRID}, author={Duan, Jie and Chow, Mo-Yuen}, year={2020}, month={Jan}, pages={281–290} }
 @article{duan_chow_2019, title={A Novel Data Integrity Attack on Consensus-Based Distributed Energy Management Algorithm Using Local Information}, volume={15}, ISSN={["1941-0050"]}, DOI={10.1109/TII.2018.2851248}, abstractNote={This paper introduces a novel data integrity attack on the well-developed consensus-based energy management algorithm. In particular, we show that by sending out elaborately falsified information during the consensus iterations, attackers could manipulate the system operating point and gain extra economic benefits. Meanwhile, the system-level and device-level constraints are still satisfied, e.g., the power generation and demand are balanced, and the operation of individual device respects physical constraints. This data integrity attack has two major features: First, attackers rely only on local information to complete the attack; neither additional information about system topology nor additional colluders are required; second, the attacking effect is accumulative, which enables attackers to choose to finish in either single or multiple iterations. By revealing such vulnerability of consensus-based applications to data integrity attack, this paper conveys the message that besides the efforts of designing novel distributed energy management algorithms to address the renewable energy integration challenges, it is equally important to protect the distributed energy management algorithms from possible malicious attacks to avoid potential economic losses. The proposed attack is illustrated in the Future Renewable Electric Energy Delivery and Management system.}, number={3}, journal={IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS}, author={Duan, Jie and Chow, Mo-Yuen}, year={2019}, month={Mar}, pages={1544–1553} }
 @article{duan_chow_2019, title={A Resilient Consensus-Based Distributed Energy Management Algorithm Against Data Integrity Attacks}, volume={10}, ISSN={["1949-3061"]}, DOI={10.1109/TSG.2018.2867106}, abstractNote={This paper addresses the vulnerability of consensus-based distributed energy scheduling algorithm to data integrity attacks. A reputation-based neighborhood-watch mechanism is introduced to detect the false information and achieve optimal operating point in the presence of misbehaving controllers. The reputation-based neighborhood watch algorithm has three major functions: 1) verifying the correctness of neighbors’ information based on two-hop shared information; 2) identifying the compromised controller based on reputation indexes; and 3) maintaining the correctness of local information estimation in the presence of false information. The effectiveness of the proposed method is illustrated through simulation analyses in the future renewable electric energy delivery and management system.}, number={5}, journal={IEEE TRANSACTIONS ON SMART GRID}, author={Duan, Jie and Chow, Mo-Yuen}, year={2019}, month={Sep}, pages={4729–4740} }
 @article{cheng_duan_chow_2018, title={To Centralize or to Distribute: That Is the Question A Comparison of Advanced Microgrid Management Systems}, volume={12}, ISSN={["1941-0115"]}, DOI={10.1109/mie.2018.2789926}, abstractNote={The advanced microgrid is envisioned to be a critical part of the future smart grid because of its local intelligence, automation, interoperability, and distributed energy resources (DER) hosting capability. The enabling technology of advanced microgrids is the microgrid management system (MGMS). In this article, we discuss and review the concept of the MGMS and state-of-the-art solutions regarding centralized and distributed MGMSs in the primary, secondary, and tertiary levels, from which we observe a general tendency toward decentralization.}, number={1}, journal={IEEE INDUSTRIAL ELECTRONICS MAGAZINE}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Cheng, Zheyuan and Duan, Jie and Chow, Mo-Yuen}, year={2018}, month={Mar}, pages={6–24} }
 @inproceedings{duan_chow_2017, title={Data integrity attack on consensus-based distributed energy management algorithm}, DOI={10.1109/pesgm.2017.8274544}, abstractNote={Over the years, the well-known consensus algorithm has been widely applied to solve the energy management problems in a fully distributed manner, due to its scalability, robustness against communication failures and privacy protection features. However, this distributed approach is vulnerable to data integrity attack as there is no control center to monitor the correctness of the shared information. In this paper, we demonstrate how a malicious attacker could manipulate the energy schedule result by sending out false information and misleading other devices in the system. This attack can lead to extra economic benefit for the attacker, while causing financial loss to the social welfare. By revealing such potential financial risks, this paper conveys the message that besides the efforts of designing novel distributed energy management algorithms, it is equally important to protect the distributed energy management algorithms from possible malicious cyber-attacks. The proposed attack is illustrated in the Future Renewable Electric Energy Delivery and Management (FREEDM) system.}, booktitle={2017 ieee power & energy society general meeting}, author={Duan, J. and Chow, M. Y.}, year={2017} }
 @inproceedings{duan_chow_2017, title={Data integrity attack on consensus-based load shedding algorithm for power systems}, DOI={10.1109/iecon.2017.8217339}, abstractNote={The paper presents a novel data integrity attack on consensus-based load shedding algorithm. In particular, we show that by sending out elaborately falsified information during the consensus iterations, attackers could manipulate the system operating point to achieve selfish goals, e.g. loads remain being served under contingencies while shedding other loads. More importantly, still maintain the system stability. This data integrity attack has three major features: 1) no additional information about system topology or other devices are required to launch the attack; 2) the attacking effect is accumulative which enables attackers to complete the attacks in either single or multiple iterations; 3) attackers could fulfill their goal using the local agent alone, no other agents need to be compromised during the attack. By revealing such potential risks, this paper conveys the message that besides the efforts of designing novel consensus-based applications, it is equally important to protect distributed smart grid applications from possible malicious cyber-attacks. The potential impact of the data integrity attacks is illustrated on simulation examples.}, booktitle={Iecon 2017 - 43rd annual conference of the ieee industrial electronics society}, author={Duan, J. and Chow, M. Y.}, year={2017}, pages={7641–7646} }
 @inproceedings{an_duan_zhang_chow_duel-hallen_2017, title={Distributed multi-step power scheduling and cost allocation for cooperative microgrids}, url={http://dx.doi.org/10.1109/pesgm.2017.8273909}, DOI={10.1109/pesgm.2017.8273909}, abstractNote={Microgrids are self-sufficient small-scale power grid systems that can employ renewable generation sources and energy storage devices and can connect to the main grid or operate in a stand-alone mode. Most research on energy-storage management in microgrids does not take into account the dynamic nature of the problem and the need for fully-distributed, multi-step scheduling. First, we address these requirements by extending our previously proposed multi-step cooperative distributed energy scheduling (CoDES) algorithm to include both purchasing power from and selling the generated power to the main grid. Second, we model the microgrid as a multi-agent system where the agents (e.g. households) act as players in a cooperative game and employ a distributed algorithm based on the Nash Bargaining Solution (NBS) to fairly allocate the costs of cooperative power management (computed using CoDES) among themselves. The dependency of the day-ahead power schedule and the costs on system parameters, e.g., the price schedule and the user activity level (measured by whether it owns storage and renewable generation devices), is analyzed for a three-agent microgrid example.}, booktitle={2017 ieee power & energy society general meeting}, publisher={IEEE Power & Energy Society General Meeting}, author={An, Lu and Duan, J. and Zhang, Y. and Chow, M. Y. and Duel-Hallen, A.}, year={2017}, pages={1–5} }
 @inproceedings{duan_zeng_chow_2016, title={An attack-resilient distributed DC optimal power flow algorithm via neighborhood monitoring}, DOI={10.1109/pesgm.2016.7741286}, abstractNote={Distributed DC optimal power flow (DC-OPF) is vulnerable to malicious cyber attacks due to the absence of a control center. In our previous work, we demonstrated a data integrity attack can manipulate the power dispatch result of distributed DC-OPF by compromising the distributed controller on a bus and modifying the information being sent to the neighboring buses. This vulnerability, in turn, could be exploited by attackers for financial arbitrage in a distributed electricity market. Thus, there is a growing need for attack-resilient control techniques that can fit into the distributed power system framework to ensure the global optimality of the power dispatch result in the presence of unexpected adversaries. In this paper, we proposed a resilient distributed DC-OPF algorithm against data integrity attacks by using a neighborhood monitoring scheme. On one hand, the resilient distributed DC-OPF algorithm is an efficient approach to deal with significant increasing amount of distributed energy resources (DERs) thanks to its flexibility and scalability. On the other hand, its neighborhood monitoring scheme enables its built-in defense to identify the misbehaving distributed controllers relying on each bus's local information and recover the optimal power dispatch from the malicious impact of data integrity attacks.}, booktitle={2016 ieee power and energy society general meeting (pesgm)}, author={Duan, J. and Zeng, W. T. and Chow, M. Y.}, year={2016} }
 @inproceedings{duan_zeng_chow_2016, title={Attack detection and mitigation for resilient distributed DC optimal power flow in the IoT environment}, DOI={10.1109/isie.2016.7744958}, abstractNote={The internet of things (IoT) is an attractive networking paradigm with machine-to-machine communication. Several distributed approaches have been proposed to solve the DC optimal power flow (DC-OPF) problem in the IoT environment. The nature of distributed computation provides scalability, robustness and privacy protection, while it also poses more vulnerabilities to unexpected cyber faults and adversaries. One important concern in the distributed DC-OPF algorithm is to maintain the optimal power dispatch result in the face of compromised nodes which are exchanging false information. In this paper, we deal with the data integrity attack and develop an attack detection and mitigation method that could fit into the IoT environment to secure the distributed DC-OPF algorithm. It is a fully distributed mechanism that enables each bus to perform the following major functions based on two-hop neighbors' information: 1) verifying the correctness of the exchanged information without infringing neighbor's privacy; 2) identifying the malicious attacker and recovering the optimal power dispatch from the malicious impact. The effectiveness of the proposed mechanism is illustrated by the standard IEEE 14-bus system.}, booktitle={Proceedings of the ieee international symposium on industrial}, author={Duan, J. and Zeng, W. T. and Chow, M. Y.}, year={2016}, pages={606–611} }
 @article{zhang_rahbari-asr_duan_chow_2016, title={Day-Ahead Smart Grid Cooperative Distributed Energy Scheduling With Renewable and Storage Integration}, volume={7}, ISSN={["1949-3029"]}, DOI={10.1109/tste.2016.2581167}, abstractNote={Day-ahead scheduling of generation units and storage devices is essential for the economic and efficient operation of a power system. Conventionally, a control center calculates the dispatch schedule by gathering information from all of the devices. However, this centralized control structure makes the system vulnerable to single point of failure and communication failures, and raises privacy concerns. In this paper, a fully distributed algorithm is proposed to find the optimal dispatch schedule for a smart grid with renewable and energy storage integration. The algorithm considers modified dc power flow constraints, branch energy losses, and energy storage charging and discharging efficiencies. In this algorithm, each bus of the system is modeled as an agent. By solely exchanging information with its neighbors, the optimal dispatch schedule of the conventional generators and energy storage can be achieved in an iterative manner. The effectiveness of the algorithm is demonstrated through several representative case studies.}, number={4}, journal={IEEE TRANSACTIONS ON SUSTAINABLE ENERGY}, author={Zhang, Yuan and Rahbari-Asr, Navid and Duan, Jie and Chow, Mo-Yuen}, year={2016}, month={Oct}, pages={1739–1748} }
 @inproceedings{duan_zeng_chow_2016, title={Resilient cooperative distributed energy scheduling against data integrity attacks}, DOI={10.1109/iecon.2016.7793846}, abstractNote={Distributed energy management algorithms eliminate the control center from the conventional energy management systems and calculate the optimal schedule for all devices through iterative coordination among neighbors. Most of the existing distributed approaches are developed under the assumption that all devices are secure and willing to achieve an optimal system performance together in a “collaborative” environment. However, unexpected faults and adversaries may emerge in the network and disrupt the convergence of those distributed approaches. In this paper, we extend the cooperative distributed energy scheduling (CoDES) algorithm to improve its resilience against data integrity attacks. Two types of data integrity attacks are considered in this paper - faulty attacks and random attacks. A distributed attack detection algorithm is developed to verify the state of neighboring devices without infringing their private information. A reputation-based mitigation algorithm is introduced to identify the compromised device and act accordingly to maintain the optimal energy scheduling result. The effectiveness of the proposed resilient distributed energy scheduling algorithm is evaluated in the Future Renewable Electric Energy Delivery and Management (FREEDM) microgrid system.}, booktitle={Proceedings of the iecon 2016 - 42nd annual conference of the ieee industrial electronics society}, author={Duan, J. and Zeng, W. T. and Chow, M. Y.}, year={2016}, pages={4941–4946} }
 @inproceedings{duan_zeng_chow_2015, title={Economic impact of data integrity attacks on distributed DC optimal power flow algorithm}, DOI={10.1109/naps.2015.7335167}, abstractNote={A variety of distributed energy management algorithms are being developed for DC optimal power flow (DCOPF) application owing to their flexibility and scalability in the presence of high distributed Energy Resources (DERs) penetration. However, these algorithms are vulnerable to malicious cyber attacks due to the absence of control centers. In this paper, we study and analyze the economic impact of the data integrity attack to distributed DC-OPF algorithms. In particular, we demonstrate how a malicious generator could gain more economic profit by compromising the distributed controller of its bus, modifying the information sent to neighboring buses and manipulating the power dispatch commands. To our best knowledge, this is the first paper to show the economic impact of malicious attacks in distributed DC-OPF. By revealing such potential financial risks, this paper conveys the message that besides the efforts of designing novel distributed energy management algorithms to address the DERs integration challenges, it is equally important to protect the distributed energy management algorithms from possible malicious attacks to avoid potential economic loss. The economic impact of the data integrity attack is illustrated in the Future Renewable Electric Energy Delivery and Management (FREEDM) system.}, booktitle={2015 north american power symposium (naps)}, author={Duan, J. and Zeng, W. T. and Chow, M. Y.}, year={2015} }